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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #330170

Research Project: Leveraging Remote Sensing, Land Surface Modeling and Ground-based Observations ... Variables within Heterogeneous Agricultural Landscapes

Location: Hydrology and Remote Sensing Laboratory

Title: Calibration of Noah soil hydraulic property parameters using surface soil moisture from SMOS and basin-wide in situ observations

Author
item SHELITTO, PETER - University Of Colorado
item SMALL, ERIC - University Of Colorado
item Cosh, Michael

Submitted to: Journal of Hydrometeorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/22/2016
Publication Date: 8/22/2016
Citation: Shelitto, P., Small, E., Cosh, M.H. 2016. Calibration of Noah soil hydraulic property parameters using surface soil moisture from SMOS and basin-wide in situ observations. Journal of Hydrometeorology. doi:10.1175/JHM-D-15-0153.1.

Interpretive Summary: Soil hydraulic properties can be retrieved from physical sampling of soil, via surveys, but this is time consuming and only as accurate as the scale of the sample. Remote sensing provides an opportunity to get pertinent soil properties at large scales, which is very useful for large scale modeling. Using the Soil Moisture Ocean Salinity mission's data record, it is possible to determine the hydraulic properties of the soil as a result of the temporal monitoring of soil moisture from this satellite. Comparisons to in situ network resources have determined that there is potential for this application. This will be useful for the weather and climate modeling community as it provides improved and more appropriate hydraulic properties estimates for large scale modeling. This is also applicable for hydrologic modelers who need to quantify hydraulic properties for the land surface as it pertains to flooding and river forecasting.

Technical Abstract: Soil hydraulic properties can be retrieved from physical sampling of soil, via surveys, but this is time consuming and only as accurate as the scale of the sample. Remote sensing provides an opportunity to get pertinent soil properties at large scales, which is very useful for large scale modeling. Using the Soil Moisture Ocean Salinity mission's data record, it is possible to determine the hydraulic properties of the soil as a result of the temporal monitoring of soil moisture from this satellite. Comparisons to in situ network resources have determined that there is potential for this application. This will be useful for the weather and climate modeling community as it provides improved and more appropriate hydraulic properties estimates for large scale modeling. This is also applicable for hydrologic modelers who need to quantify hydraulic properties for the land surface as it pertains to flooding and river forecasting.